Who We Are
We develop practical applications of
Preferred Networks (PFN) rapidly realizes practical applications of deep learning and other emerging technologies
in order to solve real-world problems that are difficult to address with existing technologies.
Making the real world computable.
With our innovative and essential technologies,
we venture into the unknown.
We make cars, robots, and other devices more intelligent by fusing software and hardware in a sophisticated manner.
By making devices intelligent enough to adapt to continuously changing environments and conditions,
our world becomes computable through real-time sensing of the physical world.
We do not compete in familiar territory, but rather take on ambitious technological challenges.
By leveraging the latest technologies, we want to advance the frontiers of knowledge and discover the world of the future.
Contributing to the world with technologies that only PFN can realize
Deep learning is a powerful and flexible solution for dealing with complicated phenomena or dynamic environments that are difficult to handle with conventional rule-based programming.
PFN’s strength is to combine a profound knowledge of deep learning together with expertise in various other fields to develop state-of-the-art technologies.
We have been engaged in challenges beyond boundaries ― from developing the core deep learning framework Chainer, to building large-scale compute clusters, to exploring a wide variety of domains (including robotics, life science, and others) ― with the aim of contributing to the world with technologies that only PFN can realize.
PFN is engaged in a variety of projects
PFN has been collaborating with FANUC to make intelligent industrial robots and machine tools since 2015, and with ENEOS to optimize and automate large-scale oil refineries since 2019.
PFN supports companies to discover innovative materials for a sustainable future through Matlantis™, a universal atomistic simulator co-developed by PFN and ENEOS Corporation.
PFN has been developing several technologies for drug discovery using its deep learning expertise and in-house computing resources. In a joint research project with Kyoto Pharmaceutical University, PFN used one of its technologies that led to the discovery of multiple lead compounds for COVID-19 treatment.
ProjectDeep Learning Frameworks
PFN develops and provides open-source deep learning libraries that support research and development in advanced, practical deep learning applications. PFN has driven the advancement of deep learning technology since June 2015 when it open-sourced Chainer™, the deep learning framework that became first in the world to adopt the define-by-run approach.